Research

Machine Learning – The ever increasing availability of data opens up new methods for scientific research and creates possibilities to deepen our understanding of nature and human behavior. My core field of research is reinforcement learning and games. Click here for our group page

Quantum Annealing Optimization Algorithms
People: Sheir Yarkoni, Florian Neukart, Thomas Bäck, Aske Plaat
Industry-relevant optimization problems may have many different forms, for example: continuous, stochastic, high-dimensional, and more. However, commercial quantum annealers can currently only solve QUBO problems, so problems need to be posed to the annealer in this form. Since finding an optimal transformation to QUBO is an NP-hard problem in itself, discovering efficient ways of generating QUBO forms for generic optimization problems is the first step in this research. We will also study Evolutionary Algorithms and Quantum Annealing.
Funding: LIACS & DWAVE 2017-

Grip on Software
People: Leon Helwerda, Aske Plaat, Fons Verbeek, Jeroen van der Leije, Frank Niessink
How can we further streamline the development of software for the government? Leiden University and ICTU are to investigate this in a joint research project that was launched on 6 July 2016. The Dutch government uses a lot of software – DigiD, for instance, or software to open and close bridges automatically. Much of that software is developed by ICTU, a Dutch government organization that helps other government institutions in the realisation of digital services.
Funding: ICTU, 2016-2020

The Computer Science challenge of calibrating the ionosphere over the SKA sky
People: Alexandar Mechev, Huub Röttgering, Huib Intema, Todor Stefanov, Aske Plaat
The ICT challenges faced by the SKA project are formidable. One of the hardest problems is how to calibrate the ionosphere to the level required by the science. The focus of this project is to build an ionospheric calibration software test-bed with which we will (i) investigate the complexity of the existing algorithms in space and time, (ii) identify bottlenecks that prevent scaling to larger data volumes, (iii) study how to modify an/or replace (parts of) the existing algorithms to overcome malicious scaling, (iv) design, implement and test such modifications or replacements.
Funding: DOME and NWO Netherlands Science Foundation, 2015-2019

Efficient Dependable Space-Borne Computing through Advanced Reconfigurability Concepts
People: Giorgio Magistrati, Gianluca Furano, Marco Rovatti, Christian Fuchs, Todor Stefanov, Aske Plaat
A spacecraft’s on-board computer (OBC) and all involved supporting components must perform a growing number of tasks within an increasingly complex system. OBCs must therefore assure consistency of both stored data and system logic at all times during the mission, providing saving and recovery mechanisms. However, hardware-side error detection and correction (EDAC) measures decline in efficiency for modern highly-scaled components due to diminishing returns when compensating with more hardware EDAC.
Funding: ESA, 2016-2020